Add to ORKGA simple linear SVM with word and character n-gram features and minimal parameter tuning can identify the gender and the language variety (for English, Spanish, Arabic and Portuguese) of Twitter users with very high accuracy. All our attempts at improving performance by including more data, smarter features, and employing more complex architectures plainly fail. In addition, we experiment with joint and multitask modelling, but find that they are clearly outperformed by single task models. Eventually, our simplest model was submitted to the PAN 2017 shared task on author profiling, obtaining an average accuracy of 0.86 on the test set, with performance on sub-tasks ranging from 0.68 to 0.98. These were the best results achieved at the compe...
In this report on our participation in the PAN shared task on author profiling, we describe our atte...
We describe the approach that we submitted to the 2015 PAN competition for the author profiling task...
We provide you with a training data set that consists of Twitter users labeled with gender. For each...
A simple linear SVM with word and character n-gram features and minimal parameter tuning can identif...
A simple linear SVM with word and character n-gram features and minimal parameter tuning can identif...
We describe our participation in the PAN 2017 shared task on Author Profiling, identifying authors’ ...
This paper describes various experiments done to investigate author profiling of tweets in 4 differe...
This paper describes an experiment done to investigate author profiling of tweets in English and Spa...
The task of analyzing a text of interest in order to find demographicinformation of an unknown autho...
We trained an SVM model on tweets to perform user profiling, in terms of gender and age, on non-Twit...
We trained an SVM model on tweets to perform user profiling, in terms of gender and age, on non-Twit...
One source of insight into the motivations of a modern human being is the text they write and post f...
In this report on our participation in the PAN shared task on author profiling, we describe our atte...
We describe the approach that we submitted to the 2015 PAN competition for the author profiling task...
We provide you with a training data set that consists of Twitter users labeled with gender. For each...
A simple linear SVM with word and character n-gram features and minimal parameter tuning can identif...
A simple linear SVM with word and character n-gram features and minimal parameter tuning can identif...
We describe our participation in the PAN 2017 shared task on Author Profiling, identifying authors’ ...
This paper describes various experiments done to investigate author profiling of tweets in 4 differe...
This paper describes an experiment done to investigate author profiling of tweets in English and Spa...
The task of analyzing a text of interest in order to find demographicinformation of an unknown autho...
We trained an SVM model on tweets to perform user profiling, in terms of gender and age, on non-Twit...
We trained an SVM model on tweets to perform user profiling, in terms of gender and age, on non-Twit...
One source of insight into the motivations of a modern human being is the text they write and post f...
In this report on our participation in the PAN shared task on author profiling, we describe our atte...
We describe the approach that we submitted to the 2015 PAN competition for the author profiling task...
We provide you with a training data set that consists of Twitter users labeled with gender. For each...